CSF Aβ42 and Aβ42/Aβ40 Ratio in Alzheimer’s Disease and Frontotemporal Dementias

Background: Alzheimer’s disease dementia (ADD) may manifest with atypical phenotypes, resembling behavioral variant frontotemporal dementia (bvFTD) and corticobasal syndrome (CBS), phenotypes which typically have an underlying frontotemporal lobar degeneration with tau proteinopathy (FTLD-tau), such as Pick’s disease, corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), or FTLD with TDP-43 proteinopathy (FTLD-TDP). CSF biomarkers total and phosphorylated tau (τT and τP-181), and amyloid beta with 42 and 40 amino acids (Aβ42 and Aβ40) are biomarkers of AD pathology. The primary aim of this study was to compare the diagnostic accuracy of Aβ42 to Aβ42/Aβ40 ratio in: (a) differentiating ADD vs. frontotemporal dementias; (b) patients with AD pathology vs. non-AD pathologies; (c) compare biomarker ratios and composite markers to single CSF biomarkers in the differentiation of AD from FTD; Methods: In total, 263 subjects were included (ADD: n = 98; bvFTD: n = 49; PSP: n = 50; CBD: n = 45; controls: n = 21). CSF biomarkers were measured by commercially available ELISAs (EUROIMMUN). Multiple biomarker ratios (Aβ42/Aβ40; τT/τP-181; τT/Aβ42; τP-181/Aβ42) and composite markers (t-tau: τT/(Aβ42/Aβ40); p-tau: τP-181/(Aβ42/Aβ40) were calculated. ROC curve analysis was performed to compare AUCs of Aβ42 and Aβ42/Aβ40 ratio and relevant composite markers between ADD and FTD, as defined clinically. BIOMARKAPD/ABSI criteria (abnormal τT, τP-181 Aβ42, and Aβ42/Aβ40 ratio) were used to re-classify all patients into AD pathology vs. non-AD pathologies, and ROC curve analysis was repeated to compare Aβ42 and Aβ42/Aβ40; Results: Aβ42 did not differ from Aβ42/Aβ40 ratio in the differentiation of ADD from FTD (AUCs 0.752 and 0.788 respectively; p = 0.212). The τT/Aβ42 ratio provided maximal discrimination between ADD and FTD (AUC:0.893; sensitivity 88.8%, specificity 80%). BIOMARKAPD/ABSI criteria classified 60 patients as having AD pathology and 211 as non-AD. A total of 22 had discrepant results and were excluded. Aβ42/Aβ40 ratio was superior to Aβ42 in the differentiation of AD pathology from non-AD pathology (AUCs: 0.939 and 0.831, respectively; p < 0.001). In general, biomarker ratios and composite markers were superior to single CSF biomarkers in both analyses. Conclusions: Aβ42/Aβ40 ratio is superior to Aβ42 in identifying AD pathology, irrespective of the clinical phenotype. CSF biomarker ratios and composite markers provide higher diagnostic accuracy compared to single CSF biomarkers.


Introduction
Over the past three decades, advances in cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers have been the defining factor in evolving the conceptual framework of Alzheimer's disease (AD) from a simple clinical entity, characterized by amnestic-predominant dementia, to a biological-clinical continuum, with diverse clinical manifestations [1]. The defining neuropathological lesions of AD are amyloid plaques (extracellular accumulation of pathologically misfolded β amyloid) and neurofibrillary tangles (consisting of hyper-phorphorylated tau protein), which result in neurodegeneration [2,3].
The AT(N) system has supported the classification of biomarkers of diverse modalities (CSF, PET, or MRI) into three groups: (A) for amyloidosis, (T) for tau-pathology, and (N) for neurodegeneration [4]. Within this framework, total tau protein (τ T ), phosphorylated tau protein at threonine 181 (τ P-181 ), and amyloid beta with 42 amino acids (Aβ 42 ) have been classified as markers of neurodegeneration, tau-pathology, and amyloidosis, respectively.
A decrease in CSF Aβ 42 is characteristic of AD. However, due to significant intersubject variability in Aβ 42 levels, defining an Aβ 42 cut-off with high diagnostic accuracy for discrimination between AD and non-AD pathologies has been problematic [5]. Moreover, Aβ 42 measurement is particularly sensitive to alterations in pre-analytical factors [6,7]. Several studies have supported that the incorporation of CSF amyloid beta with 40 amino acids (Aβ 40 ), which is a reflection of total CSF amyloid levels, by use of the Aβ 42 /Aβ 40 ratio, is a better marker of the relatively selective decrease in Aβ 42 in AD [8,9].
Most of the studies comparing the diagnostic accuracy of Ab 42 to Aβ 42 /Aβ 40 ratio have defined AD or other dementias by use of clinical criteria [10][11][12][13][14][15][16][17][18][19][20]. However, this approach is problematic, since AD may manifest with atypical non-amnestic presentations, including a language presentation (i.e., logopenic variant primary progressive aphasia), a visuospatial presentation (i.e., posterior cortical atrophy), a dysexecutive presentation (mimicking behavioral variant of frontotemporal dementia) and corticobasal syndrome [21,22]. Thus, the use of clinical criteria to define AD will result in the misclassification of AD patients as non-AD in cases of atypical manifestations and vice versa.
Several studies have compared Aβ 42 and Aβ 42 /Aβ 40 ratio to amyloid-PET, in an attempt to investigate the optimal CSF amyloid marker [8,9,[23][24][25]. Most of these studies conclude that the Aβ 42 /Aβ 40 ratio results in higher concordance with amyloid-PET compared to Aβ 42 [8,9,24,25], although a single study did not report a difference between the two markers [23]. However, most of these studies have only included healthy subjects or patients with mild cognitive impairment or dementia due to AD, without the inclusion of other dementias. To date, a study comparing CSF Aβ 42 to Aβ 42 /Aβ 40 in a cohort with neuropathological confirmation of clinical diagnoses is lacking.
The present study aimed to compare the predictive values of Aβ 42 and Aβ 42 /Aβ 40 ratio for an underlying AD pathology in a cohort of patients with diverse dementing disorders. For the purposes of this study, we selected to include patients with a clinical diagnosis of AD dementia (ADD) and various frontotemporal dementias (FTD), including behavioral variant FTD (bvFTD), progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD), as well as healthy subjects. We opted not to include patients with Lewy body dementia, due to the high incidence of co-occurrence of AD in these patients, rendering interpretation of CSF biomarkers problematic in the absence of biomarkers in other modalities (i.e., PET-CT).
Initially, the diagnostic accuracies of Aβ 42 and Aβ 42 /Aβ 40 as predictors of AD dementia were compared among study groups based on clinical diagnoses, in accordance with the methodology applied in most relevant studies. We then applied the BIOMARKAPD/ABSI criteria in all patients, irrespective of their clinical phenotype, and re-classified them as having an AD or a non-AD underlying pathology [26,27]. CSF Aβ 42 and Aβ 42 /Aβ 40 were subsequently re-applied in this setting, in order to compare their diagnostic accuracy for underlying AD pathology.

Patients
The medical files of all patients with available data on CSF biomarkers Aβ 42 , Aβ 40 , τ T , and τ P-181 , who were admitted from 2011 to 2021 to the "Neurodegenerative Disorders and Epilepsy" Ward of our hospital, were retrospectively reviewed. For the purposes of this study, subjects were included if they fulfilled the established diagnostic criteria for the following diseases: (a) ADD [21]; (b) bvFTD [28]; (c) PSP [29], and (d) CBD [30]. For comparison reasons, a control group was included. This consisted of otherwise healthy subjects, with no comorbidities, undergoing knee or hip joint surgery or hernia repair under spinal anesthesia. These subjects had a negative history of cognitive or behavioral/psychiatric disorders and no clinical evidence of any major disease. All subjects had normal scores on neuropsychological testing (Mini Mental State Examination and Frontal Assessment Battery) [31,32].

CSF Sampling and Biomarker Measurements
All patients underwent lumbar puncture at 10-11 a.m., after overnight fasting, based on standard operating procedures in accordance to recommendations to standardize preanalytical confounding factors in AD CSF biomarkers [33].
Our laboratory implements both internal and external quality control measures to ensure the accuracy of measurements longitudinally. Specifically, for internal control a pooled CSF sample is used in every test run, resulting in an over >90% between-run precision. As for external control, we participate in "The Alzheimer's Association's QC program", which provides additional external pooled CSF samples for validating results reliability regardless of the kit's lot number.
Lastly, in an effort to incorporate two CSF AD biomarkers in a single marker, the following composite markers were calculated: (a) Composite t-tau marker: τ T /(Aβ 42 /Aβ 40 ).
The τ T /Aβ 42 ratio has been previously applied as an AD neurochemical marker, based on the observed increase in τ T and decrease in Aβ 42 in patients with an underlying AD pathology. Several studies support that the Aβ 42 /Aβ 40 ratio may provide improved diagnostic accuracy for amyloid pathology compared to Aβ 42 . To look into this hypothesis, we introduced this composite marker.
The τ P-181 /Aβ 42 ratio has been previously applied as an AD neurochemical marker, based on the observed increase in τ P-181 and decrease in Aβ 42 in patients with an underlying AD pathology. As mentioned previously, substituting Aβ 42 with the Aβ 42 /Aβ 40 ratio may provide improved diagnostic accuracy for amyloid pathology. Composite p-tau marker:

Ethical Considerations
All patients or their next of kin (in cases of compromised mental capacity) provided written informed consent for participation in this study. The study was approved by the Scientific and Ethics Committee of Eginition Hospital and was performed in accordance with the guidelines of the 1964 Declaration of Helsinki.

Statistical Analysis
The normality of distribution and homogeneity of variances were checked by Shapiro-Wilk's and Levene's tests, respectively. Comparison of clinical, neuropsychological, and CSF biomarker characteristics between study groups was performed by ANOVA (with Bonferroni correction for multiple comparisons) or Kruskal-Wallis test as appropriate.
We performed two sets of analyses. The initial analysis was based on the clinical diagnoses of the study subjects. Thus, Receiver Operating Characteristic (ROC) Curve analysis was performed to compare the diagnostic accuracy of all CSF biomarkers, biomarker ratios, and composite biomarkers in differentiating between patients with AD dementia vs. all other clinical groups. Area under the curve (AUC), 95% confidence interval of the AUC, cut-off point with optimal diagnostic accuracy (defined as maximal sensitivity and specificity), as well as specificity, sensitivity, and Youden Index (YI) of optimal cut-off points, were calculated.
In order to look into possible differences between AUCs of ROC curves of various biomarkers in the identification of AD dementia, the De Long method was applied. In an effort to compare the diagnostic accuracy of Aβ 42 vs. Aβ 42 /Aβ 40 ratio, the following comparisons of ROC curves were performed: (a) Aβ 42 vs. Aβ 42 /Aβ 40 ratio; (b) τ T /Aβ 42 vs. composite t-tau: (c) τ P-181 /Aβ 42 vs. composite p-tau.
The second analysis aimed to investigate the diagnostic accuracy of single CSF biomarkers, biomarker ratios, and composite biomarkers in identifying AD pathology irrespective of the clinical phenotype. To this end, a two-step process was applied, as described elsewhere.
We elected to apply the most stringent classification criterion (i.e., all three CSF biomarkers abnormal) for AD pathology identification in order to increase specificity, at the expense of sensitivity. For amyloid pathology (A) in particular, there were two available established CSF markers: Aβ 42 and the Aβ 42 /Aβ 40 ratio. In an effort to increase specificity, subjects with a decrease in both markers (Aβ 42 and Aβ 42 /Aβ 40 ) were considered A(+), and only subjects with normal values in both biomarkers were considered A(−). Of the 263 subjects, 22 (8.4%; AD dementia: 16 patients; CBD: 3 patients; PSP: 1 patients; controls: 2 subjects) had discrepant results in amyloid pathology identification based on Aβ 42 and Aβ 42 /Aβ 40 ratio and were excluded from this analysis.
Thus, this second analysis included 82 patients with AD pathology and 140 patients with non-AD pathology: 49 bvFTD patients, 42 CBD patients, and 49 PSP patients. The majority of the non-AD pathology patients are considered to have an underlying frontotemporal lobar degeneration (FTLD), with most PSP and CBD patients harboring an FTLD with tau proteinopathy (FTLD-tau) and most bvFTD patients harboring either an FTLD-tau or FTLD-TDP43 proteinopathy. Thus, in essence, the second analysis referred to a comparison of Aβ 42 to Aβ 42 /Aβ 40 ratio in the differentiation of AD pathology from FTLD. However, due to the lack of neuropathological confirmation, we elected to use the term non-AD pathology instead of FTLD, since the presumed underlying pathology is based on CSF biomarker profiles.
Following this classification of all subjects irrespective of their phenotype into the AD and nonAD groups, ROC curve analysis was applied to determine the discriminative power of CSF biomarkers, biomarker ratios, and composite markers for this differentiation. Cut-off points were determined based on the maximal combined sensitivity and specificity criterion. Area under the curve (AUC), 95% confidence interval of the AUC, YI, sensitivity, and specificity were also calculated. In order to look into possible differences between AUCs of ROC curves of various biomarkers in AD pathology identification, the De Long method was applied. In an effort to compare the diagnostic accuracy of Aβ 42 vs. Aβ 42 /Aβ 40 ratio, the following comparisons of ROC curves were performed: (a) Aβ 42 vs. Aβ 42 /Aβ 40 ratio; (b) τ T /Aβ 42 vs. composite t-tau: (c) τ P-181 /Aβ 42 vs. composite p-tau.

Clinical and Demographic Data
In total, 263 subjects were included (ADD: 98 patients; bvFTD: 49 patients; PSP: 50 patients; CBD: 45 patients; controls: 21 subjects). Study groups differed in age (p = 0.003), with the control group exhibiting the greatest age compared to other groups and sex distribution (p = 0.005). Control subjects performed significantly better in the MMSE and FAB tests compared to patient groups, as expected (p < 0.001) ( Table 1).

ROC Curve Analysis of CSF Biomarkers for the Differentiation between AD vs. Non-AD Pathology, Irrespective of Clinical Phenotype
The composite t-tau marker provided a maximal AUC of 0.985 for the differentiation of AD pathology from non-AD pathologies, with a cut-off of >5.82 resulting in a 100% sensitivity and 91.2 specificity. The p-tau markers provided comparable AUCs of 0.965. Among CSF biomarker ratios, the τ T /Aβ 42 resulted in maximal AUC (0.975) followed by τ P-181 /Ab 42 , Aβ 42 /Aβ 40 , and τ P-181 /τ T ratios (AUCs: 0.952, 0.939, and 0.780, respectively).

Discussion
The primary aim of this study was to compare the predictive value of Aβ 42 /Aβ 40 ratio to Aβ 42 in identifying: (a) Alzheimer's disease dementia (ADD) from other clinical phenotypes and (b) Alzheimer' disease pathology from non-AD pathologies. Regarding the clinical distinction of ADD from other phenotypes, the Aβ 42 /Aβ 40 ratio and Aβ 42 provided comparable diagnostic accuracy in our cohort. In agreement with our study, most relevant studies in the literature relying on clinical criteria for AD definition support that the Aβ 42 /Aβ 40 ratio provides greater AUC values compared to Aβ 42 in diagnosing ADD [12][13][14][15][16][17][18][19][20]. Few studies, however, have conflicting results, supporting the superiority of Aβ 42 over theAβ 42 /Aβ 40 ratio or no difference between the two markers [10,11]. Importantly, contrary to our study, these studies do not include statistical comparisons of AUC values and rely on numerical differences between AUCs.
Importantly, the Aβ 42 /Aβ 40 ratio provided significantly greater diagnostic accuracy compared to Aβ 42 in the differentiation of AD pathology from non-AD pathologies. Likewise, Aβ 42 /Aβ 40 -derived composite markers produced greater AUCs τo Aβ 42 -derived ratios, although these differences did not reach statistical significance. Due to the inclusion in the present study of phenotypes that typically have an underlying FTLD pathology, either with tau proteinopathy (FTLD-tau) or TDP-43 (FTLD-TDP), this finding signifies the importance of the Aβ 42 /Aβ 40 ratio in differentiating between AD pathology and FTLD. However, this finding needs verification by studies with both CSF biomarker and neuropathological data available. This finding is particularly important from a clinical and research perspective because it highlights the importance of the Aβ 42 /Aβ 40 ratio in the in vivo identification of amyloid pathology in patients with diverse clinical phenotypes. Most studies comparing CSF biomarkers to amyloid-PET support this finding [8,9,24,25], although a study reported conflicting results, depending on the assay used [23].
A third finding of our study is the significant disparity between clinical diagnosis and underlying pathology, highlighting the significant clinical heterogeneity of AD [21,22] as well as the significant pathological heterogeneity of phenotypes such as CBS [35,36].
Multiple clinical-pathological studies have supported this clinical-pathological overlap [37][38][39][40]. However, this disparity was particularly high for ADD patients in our cohort (47% of ADD patients had a CSF AD profile, 16% had discrepant results and 37% had non-AD pathologies) and exceedingly low for bvFTD (all patients had non-AD CSF profile).
This finding can be attributed to the criteria we applied for the definition of the CSF AD biochemical profile. We elected for the purposes of this study to define the AD CSF profile according to the BIOMARKAPD/ABSI criteria, which require all three major biomarker groups (amyloid, tau, and neurodegeneration) to be abnormal. Additionally, we elected to define as A(+) patients with abnormal values in both Aβ 42 and Aβ 42 /Aβ 40 ratio. These stringent criteria were applied to enhance the specificity of AD classification at the expense of sensitivity, in the absence of other biomarkers such as amyloid PET, and with no neuropathological data available. Thus, the classification of patients in AD or non-AD pathologies do not reflect the routine clinical practice, wherein a single amyloid CSF biomarker is sufficient to characterize the (A) status in the ATN system, and patients with A(+)T(+)N(−) are classified as AD. To support this hypothesis, when applying the ATN criteria based on Aβ 42 /Aβ 40 ratio, 72% of patients were classified as AD pathology (data not shown).
In CSF biomarker studies looking into inherent differences among neurodegenerative disorders, the significant clinical-pathological overlap in neurodegenerative disorders can be overcome if a two-step algorithm is applied, as proposed previously [41,42]. As a first step, all patients, irrespective of their clinical phenotype, should initially be classified as AD or non-AD based on a biomarker taxonomic system (e.g., ATN or BIOMARKAPD/ABSI). This will assist in identifying atypical presentations of AD (e.g., PPA, behavioral-frontal dementia, CBS, etc.) and avoid misclassification of these subjects. The second step would involve the direct comparison of biomarker levels among different disorders.
An interesting finding was the improved diagnostic accuracy of CSF biomarker ratios and composite markers compared to single CSF biomarkers. The τ T /Aβ 42 ratio and the composite markers (t-tau and p-tau composite marker) provided excellent discriminative power for AD pathology identification. Although these ratios and composite markers lack inherent biological meaning, the incorporation of two biomarkers (in the case of CSF biomarker ratios) or three biomarkers (in the case of composite markers) in a single continuous variable for each patient increases discriminative power compared to single CSF biomarkers. To this extent, CSF biomarker ratios have been previously implemented and have yielded excellent concordance with neuropathological data in FTD [43,44]. Additionally, CSF ratios were superior to single CSF biomarkers in the differential diagnosis of AD from bvFTD [43,[45][46][47].
An additional theoretical advantage of using CSF biomarker ratios and composite markers instead of single CSF biomarkers is that they may assist in decreasing the intersubject variability in pre-analytical variables, such as type of sampling and storage tubes, incubation time, number of freeze/thaw cycles, type of pipettes used, etc. This has previously been proven for the Aβ 42 /Aβ 40 ratio [6,7].
The present study has certain limitations. Firstly, our cohort, as is the case with all relevant studies in the literature, lacks neuropathological confirmation, which is the golden standard for diagnosis in neurodegenerative disorders. For this reason, we only included well-characterized patients based on the most recently established diagnostic criteria with adequate follow-up. A second limitation is the absence of a biomarker of a different modality (e.g., amyloid PET), to use as a reference. However, PET-CT can only provide information on a single axis of the ATN triad. For this reason, we selected to apply the BIOMARKAPD/ABSI criteria, to classify patients into AD or non-AD pathologies. Additionally, in order to minimize the effect of cyclical error in comparing Aβ 42 τo Aβ 42 /Aβ 40 , we used all four major AD CSF biomarkers for AD classification (Aβ 42 , Aβ 42 /Aβ 40 ratio, τ T , and τ P-181 ).
Our study, in accordance with the literature, supports the improved diagnostic accuracy of the Aβ 42 /Aβ 40 ratio compared to Aβ 42 in identifying AD pathology. Moreover, we highlighted the exceptionally high diagnostic accuracy of composite markers. Further studies, with neuropathological confirmation, are needed, to establish the correlation between CSF biomarkers and neuropathological characteristics. Informed Consent Statement: Written informed consent for participation in this study was provided by all patients or their next of kin in cases of compromised mental capacity.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author.